Method for monitoring occupancy in a work area

ABSTRACT

One variation of a method for monitoring occupancy in a work area includes, at a sensor block: transitioning from an inactive state into an active state when an output of a motion sensor indicates motion in a work area; during a scan cycle in the active state, recording an image through an optical sensor at a time, detecting a set of humans in the image, detecting a second set of human effects in the image, predicting a second set of humans occupying but absent the work area based on the second set of human effects, and estimating a total occupancy in the work area at the time based on the set of humans and the second set of humans; and transmitting the total occupancy to a remote computer system for update of a scheduler for the work area.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application is a continuation application of U.S. patentapplication Ser. No. 16/828,676, filed on 24 Mar. 2020, which is acontinuation-in-part application of U.S. patent application Ser. No.16/424,252, filed on 28 May 2019, which is a continuation application ofU.S. patent application Ser. No. 15/973,445, filed on 7 May 2018, whichclaims the benefit of U.S. Provisional Application No. 62/502,132, filedon 5 May 2017, each of which is incorporated in its entirety by thisreference.

TECHNICAL FIELD

This invention relates generally to the field of occupancy monitoringand more specifically to a new and useful method for monitoringoccupancy in a work area in the field of occupancy monitoring.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a flowchart representation of a method;

FIG. 2 is a flowchart representation of one variation of the method;

FIGS. 3A and 3B are flowchart representations of one variation of themethod; and

FIG. 4 is a flowchart representation of one variation of the method.

DESCRIPTION OF THE EMBODIMENTS

The following description of embodiments of the invention is notintended to limit the invention to these embodiments but rather toenable a person skilled in the art to make and use this invention.Variations, configurations, implementations, example implementations,and examples described herein are optional and are not exclusive to thevariations, configurations, implementations, example implementations,and examples they describe. The invention described herein can includeany and all permutations of these variations, configurations,implementations, example implementations, and examples.

1. Method

As shown in FIGS. 1 and 4 , a method S100 for monitoring occupancy in awork area includes: at a sensor block, transitioning from an inactivestate into an active state in Block S110 in response to an output of amotion sensor, integrated into the sensor block, indicating motion in afield of view of an optical sensor integrated into the sensor block, thefield of view encompassing the work area; during a first scan cycle inthe active state, recording a first image through the optical sensor ata first time in Block S120; detecting a first set of humans in the firstimage in Block S130, detecting a second set of human effects in thefirst image and predicting a second set of humans occupying but absentthe work area based on the second set of human effects in Block S132;and estimating a first total occupancy in the work area at the firsttime based on the first set of humans and the second set of humans inBlock S140; and transmitting the first total occupancy to a remotecomputer system for update of a scheduler for the work area in BlockS150.

As shown in FIG. 1 , one variation of the method S100 includes: at asensor block, transitioning from an inactive state into an active statein response to a motion sensor, integrated into the sensor block,detecting a motion event within the conference room in Block S110;during a first scan cycle in the active state, recording a first imagethrough an optical sensor—integrated into the sensor block and defininga field of view intersecting the conference room—at a first time inBlock S120 and detecting a first set of humans in the first image inBlock S130; transmitting the first total occupancy to a remote computersystem for update of a scheduler for the conference room in Block S150;during a second scan cycle succeeding the first scan cycle in the activestate, recording a second image through the optical sensor at a secondtime in Block S120 and detecting absence of humans in the second imagein Block S130; and, in response to lack of outputs from the motionsensor indicating motion in the conference room for more than athreshold duration and detecting absence of humans in the second image,transmitting confirmation of vacancy in the conference room to theremote computer system for update of the scheduler for the conferenceroom in Block S150 and transitioning from the active state into theinactive state in Block S112.

As shown in FIGS. 3A and 3B, another variation of the method S100includes: at a sensor block, transitioning from an inactive state intoan active state in Block S110 in response to a motion sensor, integratedinto the sensor block, detecting a motion event within the agile workenvironment; during a first scan cycle in the active state, recording afirst image through an optical sensor, integrated into the sensor blockand defining a field of view containing a set of agile desks within theagile work environment, at a first time in Block S120; detecting a firstset of humans in the first image in Block S130; interpreting proximityof the first set of humans, detected in the first image, to locations ofa first subset of agile desks, in the set of agile desks, as occupancyof the first subset of agile desks at the first time in Block S140;detecting a second set of human effects in the first image in BlockS132; interpreting proximity of the second set of human effects,detected in the first image, to locations of a second subset of agiledesks in the set of agile desks and absence of humans proximal thesecond subset of agile desks as absent occupancy of the second subset ofagile desks at the first time in Block S140; and transmittingconfirmation of occupancy of the first subset of agile desks and thesecond subset of agile desks to a remote computer system for update of ascheduler for the agile work environment in Block S150.

2. Applications

Generally, the method S100 can be executed within a work area—such aswithin a conference room, an agile work environment, a cafeteria, or alounge, etc. within a facility—to monitor changes in human occupancy inthe work area, to update schedulers or managers for assets and spaceswithin the work area, and to control various actuators throughout thework area based on these changes in human occupancy. As shown in FIG. 2, Blocks of the method S100 can be executed by a system including: apopulation of sensor blocks deployed throughout the facility; a remotecomputer system that updates schedulers, serves prompts for managers oradministrators based on occupancy changes and states of spaces withinthe work area, and/or triggers various actuators within the facilitybased on data received from this population of sensor blocks; and localgateways arranged throughout the facility and configured to pass databetween these sensor blocks and the remote computer system.

In particular, each sensor block can include an optical sensor (e.g., acamera; and various other sensors) and can be configured to mount to awall, ceiling, or other surface within the field of view of the opticalsensor facing an area of interest within the facility. For example, asensor block an be arranged overhead and facing downward over aconference table in a conference room or arranged overhead and facingdownward over a cluster of desks in an agile work environment within thefacility. The sensor block can implement Blocks of the method S100 torecord an image of an area of interest within the facility and tolocally extract various insights from this image, such as locations andstates of humans, desks, chairs, conference rooms, etc. within the areaof interest. The sensor block can then upload these extracteddata—rather than raw image data—to the remote computer system.

In particular, the sensor block can locally implement a computer visionand/or artificial intelligence module to compress this image intonon-visual quantitative or qualitative insights or commands and offloadthese non-visual insights or commands for handling by the remotecomputer system or other affiliated systems to the exclusion of visualdata recorded by the sensor block. The sensor block can regularly repeatthis process of recording an image, extracting non-visual insights orcommands from this image, and offloading these non-visual insights orcommands throughout its operation in order to enable the remote computersystem or other affiliated systems to respond to various events andchanges within the work environment in (near) real-time.

Furthermore, by transmitting quantitative and qualitative insightsextracted from an image—recorded by the sensor block—to the remotecomputer system rather than transmitting these images directly, thesensor blocks can preserve privacy for humans occupying the facility andensure that operations and data moving inside the facility remain securewhile also enabling the remote computer system to track humans, assets,and states of work areas throughout the facility.

As described below, a sensor block executing Blocks of the method S100can also be battery-powered and can wirelessly transmit data to a localgateway, which passes these data to the remote computer system. Sensorblocks in this configuration may reduce or eliminate a burden ofdeploying various sensors throughout the facility by eliminating a needfor fixed and power infrastructure at target sensor block locationsthroughout the facility and may thus enable rapid deployment (andredistribution) of sensor blocks throughout the facility.

However, to maximize battery life and thus limit maintenance for sensorblocks deployed throughout the facility, a sensor block can remain in aninactive (e.g., a “very-low-power” state) by default. However, when apassive motion sensor in the sensor block detects motion in the field ofview of the sensor block, the sensor block can transition from theinactive state into an active state. While in the active state, thesensor block can record images, extract data from these images, andwirelessly transmit these data to a local gateway during intermittentscan cycles between periods of low-power operation. The sensor block canthen transition back into the inactive state when the motion sensor nolonger detects motion and when the sensor block detects no humans in alast image recorded by the sensor block. In particular, the sensor blockcan leverage a passive motion sensor to trigger transition into ahigher-power, active state; however, even in the active state, thesensor block can operate predominately in a low-power state and onlyintermittently execute higher-power functions—including recording animage, processing this image, and/or wirelessly broadcasting dataextracted from this image back to a gateway or remote computersystem—such as on a ten-minute interval.

The sensor block can thus limit overall power consumption overtime—which may peak during periods of image capture, image processing,and wireless data transmission (hereinafter “scan cycles”)—while also:intelligently collecting recording images of a work area in the facilitywhen such data extracted from these images may be most relevant tooperation of the facility; collecting these data at a frequencycoordinated (e.g., matched) to value of these data to operation and useof the facility; and/or intelligently offloading these data to theremote computer system (or to the gateway) when these data areimmediately relevant to operation of the facility.

The population of sensor blocks installed throughout the facility cantherefore locally execute Blocks of the method S100 to detect humans andassets moving throughout the facility, identify states of these humansand assets, and quantify or qualify use of various spaces and assetsthroughout the facility based on images recorded by these sensor blocksover time. By returning non-visual, quantitative and/or qualitative dataextracted from these images, these sensor blocks can enable the remotecomputer system and/or other affiliated systems to update variousschedulers (e.g., a conference room manager, an agile desk manager) orcontrol various actuators (e.g., HVAC controls) within the facility,thereby improving operating efficiency of the facility, improvingcomfort of occupants within the facility, and/or improving productivityof occupants within the facility over time.

The method S100 is described below as executed by one sensor block inconjunction with one gateway and one remote computer system. However,the remote computer system can interface with any other number ofgateways and any other number of sensor blocks—executing Blocks of themethod S100—deployed throughout the facility.

2.1 Terms

The method S100 is described herein as executed by a system to detect oridentify “human effects” proximal to a conference room, an agile desk inan agile work environment, or other work surface within the field ofview of the optical sensor in the sensor block. The system can detect“human effects” that can include personal items or other objects carriedby humans in a work environment and that are detectable via Blocks ofthe method S100 described below. These detectable “human effects” orpersonal items can include but are not limited to: laptop computers;tablet computers; smartphones, keyboards; electronic mice; chargingand/or data transfer cables; beverage and/or food containers such aslunch boxes, thermoses, coasters; utensils such as plates, bowls, forks,knives, spoons; tissues, napkins and/or other sanitary supplies;personal fans; headphones; earphones; paperweights; staplers; personalplants; clothing such as shoes, jackets, hats, and/or other wearableaccessories; eye glasses; glasses cleaners; glasses cases; virtualreality goggles; seat cushions; tools such as hand tools and straightedges; keys and keychains; wallets; pens or pencils; erasers; books;booklets; notebooks; notepads; sticky-notes; loose paper; organizationaltools such as mail trays, folders, and/or binders; lamps; clocks; and/orwhiteboards.

Additionally, the system can identify intransient assets (i.e. fixedassets) or transient assets (i.e. mobile assets) that are independent ofhuman occupancy of a desk or conference room. More specifically, thesystem can: access a list of assets or a template image of each assetthat is present, by default (e.g., provided by an administrator of thework environment), within an agile work environment or in a conferenceroom (e.g., such as a computer monitor or laptop docking station).Therefore, the system can, in response to detecting these assets at adesk or conference room, exclude these assets from classification as a“human effect.” Thus, the system can identify and detect “human effects”as the personal items or objects listed above excluding objects (such asmobile assets or fixed assets) provided to the work environment byadministrators or employers in the work environment.

Furthermore, the system can also classify unidentifiable objects as“human effects” based solely on these object's context within imagesrecorded by the system. More specifically, the system can, in responseto failure to identify an object as a “human effect,” a mobile asset, ora fixed asset, classify objects as “human effects” based on the presenceof these objects on a desk, in a conference room, or proximal to anotherobject classified as a “human effect” without specifically classifyingthe object as one of the categories of “human effects” described above.Thus, the system can classify an unidentifiable object as a “humaneffect” based only on the object's location relative to other detectedobjects or features within an image of an agile work environment or aconference room.

The method S100 is described herein as executed by a system to detecthumans and human effects “proximal” or “proximal to” objects orlocations within a work environment. Generally, the phrase “a firstobject proximal to a second object” refers to presence of the firstobject within a threshold distance (e.g., two meters) of the secondobject or within a predefined area associated with the second object(e.g., a surface of a desk and a rectangular area in front of the desk).The system can execute Blocks of the method S100 in response todetecting objects within a threshold distance or predefined area definedin association with the particular objects described as “proximal to”one another. In one example, the system can detect or identify“proximity” of a human or human effect to a desk within a workenvironment in response to the human or the human effect being locatedwithin three feet of the outer edge of the desk and desk chairassociated with the desk. In another example, the system can detect oridentify “proximity” of a human or a human effect in response to thehuman or the human effect being located within a predefined areadelimited by a five-foot by eight-foot region overlapping the front ofthe desk. In yet another example, the system can detect or identify“proximity” of a human or human effect to a desk within a workenvironment in response to the human or the human effect being locatedwithin a statistically relevant area around the desk as indicated bymachine learning models utilized to detect occupancy at the desk. In anadditional example, the system can detect or identify “proximity”between two objects, both located on the surface of a desk in responseto a first object being located within a ten-centimeter radius of asecond object. Thus, the system can detect that a first object is“proximal” or “proximal to” a second object based on the specificobjects being detected and these objects' context relative to the agilework environment.

3. Sensor Block

As shown in FIG. 2 , a sensor block can include: an optical sensordefining a field of view; a motion sensor configured to detect motion inor near the field of view of the optical sensor; a processor configuredto extract data from images recorded by the optical sensor; a wirelesscommunication module configured to wirelessly transmit data extractedfrom images; a battery configured to power the optical sensor, theprocessor, and the wireless communication module over an extendedduration of time (e.g., one year, five years); and an housing configuredto contain the optical sensor, the motion sensor, the processor, thewireless communication module, and the battery and configured to mountto a surface within the field of view of the optical sensor intersectingan area of interest within the facility (e.g., a conference table withina conference room, a cluster of agile desks in an agile workenvironment)

The optical sensor can include: a color camera configured to record andoutput 2D color images; and/or a depth camera configured to record andoutput 2D depth images or 3D point clouds. However, the optical sensorcan define any other type of optical sensor and can output visual oroptical data in any other format.

The motion sensor can include a passive infrared sensor (or “PIR”sensor) that defines a field of view that overlaps the field of view ofthe optical sensor and that passively outputs a signal representingmotion within (or near) the field of view of optical sensor. Asdescribed above, the sensor block can transition from an inactive stateto an active state in Block S110 responsive to an output from the motionsensor indicating motion in the field of view of the motion sensor; thesensor block can then trigger the optical sensor to record an image(e.g., a 2D color image), which may capture a source of the motiondetected by the motion sensor.

In one example, the motion sensor is coupled to a wake interrupt pin onthe processor. However, the motion sensor can define any other type ofmotion sensor and can be coupled to the processor in any other way.

In one variation, the sensor block also includes: a distance sensor(e.g., a 1D infrared depth sensor); an ambient light sensor; atemperature sensor; an air quality or air pollution sensor; and/or ahumidity sensor. However, the sensor block can include any other ambientsensor. In the active state, the sensor block can sample and record datafrom these sensors and can selectively transmit these data—paired withinsights extracted from images recorded by the sensor block—to a localgateway in Block S150. The sensor block can also include a solar cell orother energy harvester configured to recharge the battery.

The processor can locally execute Blocks of the method S100, asdescribed above and below, to selectively wake responsive to an outputof the motion sensor, to trigger the optical sensor to record an image,to write various insights extracted from the image, and to then queuethe wireless communication module to broadcast these insights to anearby gateway for distribution to the remote computer system when theseinsights exhibit certain target conditions or represent certain changes.

The optical sensor, motion sensor, battery, processor, and wirelesscommunication module, etc. can be arranged within a single housingconfigured to install on a flat surface—such as by adhering ormechanically fastening to a wall or ceiling—with the field of view ofthe optical sensor facing outwardly from the flat surface andintersecting an area of interest within the facility.

However, this “standalone,” “mobile” sensor block can define any otherform and can mount to a surface in any other way.

3.1 Wired Power and Communications

In one variation, the sensor block additionally or alternativelyincludes a receptacle or plug configured to connect to an external powersupply within the facility—such as a power-over-Ethernet cable—andsources power for the optical sensor, processor, etc. from this externalpower supply. In this variation, the sensor block can additionally oralternatively transmit data—extracted from images recorded by the sensorblock—to the remote computer system via this wired connection (i.e.,rather than wirelessly transmitting these data to a local gateway).

4. Local Gateway

As shown in FIG. 2 , the system can also include a local gateway:configured to receive data transmitted from sensor blocks nearby viawireless communication protocol or via a local ad hoc wireless network;and to pass these non-optical data to the remote computer system, suchas over a computer network or long-range wireless communicationprotocol. For example, the gateway can be installed near and connectedto a wall power outlet and can pass data received from a nearby sensorblock to the remote computer system in (near) real-time. Furthermore,multiple gateways can be installed throughout the facility and caninterface with many sensor blocks installed nearby to collect data fromthese sensor blocks and to return these data to the remote computersystem.

In one variation, a sensor block transmits a (raw or compressed)image—recorded by the optical sensor in the sensor block during a scancycle executed by the sensor block while in the active state—to a nearbygateway, and the gateway executes the method S100 and techniquesdescribed above and below to extract insights from this image and toreturn these insights to the remote computer system (e.g., sans the rawor compressed image).

5. Remote Computer System

As shown in FIGS. 2, 3A, and 3B, the remote computer system—such as aremote server—can receive non-optical data from one or more gatewaysinstalled in the facility (or directly from sensor blocks) and canmanipulate these non-optical data to update schedulers for variousspaces or assets in the facility in Block S160, to selectively triggerassistance or maintenance in certain areas of the facility, and/orcontrol various actuators coupled to the facility in Block S170 based onthese data, as described below.

6. Sensor Block Transition from Inactive State to Active State

Block S110 of the method S100 recites, at the sensor block,transitioning from an inactive state into an active state in response toan output of a motion sensor—integrated into the sensor block—indicatingmotion in a work area (e.g., a field of view of an optical sensorintegrated into the sensor block). Generally, in Block S110, the sensorblock can transition from an inactive state (e.g., a “low-power,” sleep,or hibernate mode) into an active state when the passive motion sensordetects motion nearby (e.g., in the field of view of the opticalsensor), since this motion may indicate a state change of the work area,state change of an asset in the work area, and/or presence of a human inthe work area.

7. Scan Cycle

As shown in FIGS. 1, 3B, and 4 , to execute a scan cycle in the activestate, the sensor block can: record a first image through the opticalsensor at a first time in Block S120; detect a first set of humans inthe first image in Block S130; detect a second set of human effects(e.g., a computer, a coffee cup, a coat, a notebook, etc.) in the firstimage and predict a second set of humans occupying but absent the workarea based on the second set of human effects in Block S132; and thenestimate a first total occupancy in the work area at the first time inBlock S140 based on the first set of humans and the second set ofhumans. Generally, while in the active state, the sensor block canexecute a series of scan cycles between periods of low-power operationto calculate a series of total occupancy estimates for the work area inBlocks S130, S132, and S140. To minimize power consumption in the activestate, the sensor block can execute each scan cycle in less than a firstduration of time (e.g., in less than ten seconds) and return to alow-power mode during a second, longer duration (e.g., on a five-, ten-,or thirty-minute interval) before executing a next scan cycle.

In one implementation, the sensor block can immediately enter the activestate in Block S110 and execute a scan cycle once the motion sensordetects motion, such as within five seconds of the sensor block enteringthe active state following detected motion in its field of view, inBlock S120. Alternatively, in response to transitioning from theinactive state into the active state (or following detecting motion inits field of view), the sensor block can: set a delay timer for aduration associated with aggregation of humans in the work area (e.g.,thirty seconds for the sensor block installed over a kitchen, one minutefor the sensor block installed over an agile work environment, or twominutes for the sensor block installed in a conference room); and thenexecute a first scan cycle during this active state period only once thedelay time expires.

During a scan cycle, the sensor block can: record an image; (sample andrecord values from other ambient sensors in the sensor block) in BlockS120; and process the image to extract frequencies, locations,orientations, qualities, and/or states of humans and assets in the image(as described further below) in Blocks S130, S132, and S140. In oneimplementation, the sensor block: implements computer vision techniquesto detect and identify discrete objects (e.g., humans, human effects,mobile assets, and/or fixed assets) in an image recorded by the opticalsensor during a scan cycle; and implements a rule or context engine tomerge types, postures, and relative positions of these objects intostates of rooms, humans, and other objects. For example, the sensorblock can implement object recognition, template matching, or othercomputer vision techniques to detect and identify objects in the image.

Alternatively, the sensor block can implement artificial intelligencetechniques to extract states of rooms, humans, and/or objects directlyfrom an image recorded during the scan cycle. For example, the sensorblock can store and implement one or more artificial intelligencemodels—trained on labeled past images of the same work environmentand/or work environments in other facilities—to interpret states ofrooms, humans, and objects in an image recorded by the sensor blockduring a scan cycle. Similarly, in the application described below inwhich the sensor block is installed over an agile work environment anddetects a first set of humans in an image, detects a second set of humaneffects in the image, and predicts a second set of humans occupying butabsent the agile work environment based on the second set of humaneffects during a scan cycle, the sensor block can execute an artificialintelligence model locally on the sensor block to extract these featuresfrom the image and to interpret these features as a total occupancy in aregion of the agile work environment—in the field of view of the opticalsensor—at the time the image was recorded.

In the foregoing implementations, the sensor block can detect ordistinguish humans directly from features extracted from an imagerecorded during the current scan cycle in Block S130. In Block S132, thesensor block can additionally or alternatively: detect human effects,such as clothing (e.g., a coat), a computing device (e.g., a smartphone,a tablet, a laptop computer), a notebook, and/or coffee cup, etc.; groupthese human effects into clusters based on proximity; and then interpreta cluster of human effects as occupancy of one human who is not presentin the field of view of the optical sensor at the time the image wasrecorded but who may intend to return to the location of this cluster inthe future, such as to collect these human effects, to rejoin a meeting,or to resume working.

The sensor block can also distinguish various fixed and/or mobile assetsin the image, such as tables, desks, chairs, whiteboards, monitors ortelevisions, and/or cabinets, etc. The sensor block can then derive astate of a human occupying—and present or not present at—a locationwithin the field of view of the optical sensor based on types andrelative positions of these assets to the human's location (or to thelocation of a cluster of human effects interpreted as a unique human).For example, the sensor block can determine whether the human is workingindependently, eating, conversing, conferencing, walking, standing,sitting, etc. based on the human's posture, proximity of human effectsand assets to the human, proximity of other humans to the human, and/orother features extracted from one image or from a series of imagesrecorded by the sensor block during one scan cycle.

However, the sensor block can implement any other method or technique toqualify or quantify presence and/or occupancy of humans, human effects,mobile and fixed assets, and states of spaces within the field of viewof the sensor block in Blocks S130 and S132.

At the conclusion of a scan cycle, the sensor block can also wirelesslytransmit these insights extracted from the image, commands (e.g., HVACcommands, lighting commands, maintenance requests) generated locally bythe sensor block based on these insights, and/or raw ambient sensor databack to a local gateway. Alternatively, the sensor block can store theseinsights locally (e.g., in a cache or buffer) and withhold wirelesstransmission of these data. The sensor block can then transmit datastored in the cache or buffer following a later scan cycle in which thesensor block detects certain trigger conditions in its field of view,such as a change in occupancy, a change in meeting quality, or athreshold change in asset entropy in the work area, as described below.

Upon completing a scan cycle, the sensor block can set a dwell timer foran interval between scan cycles and then enter a low-power mode, asshown in FIG. 4 . When the dwell timer expires, the system can awake,execute a scan cycle, and then return to the low-power mode. The sensorblock can repeat this process until the motion sensor detects no motionin the work area for a threshold duration of time and/or until theprocessor detects no humans in the field of view of the optical sensor.

8. Sensor Block Transition from Active State to Inactive State

In the active state, the sensor block can also record a last time of anoutput of the motion sensor that indicates motion in the work area. Ifthis last time precedes a current time by more than a thresholdduration, the sensor block can execute a scan cycle—such as outside of apreset time interval between consecutive scan cycles—to record a testimage through the optical sensor and to scan the test image for humansand/or human effects. If the sensor block then detects—in the testimage—absence of humans and absence of human effects that may otherwiseindicate human occupancy in the work area in the field of view of thesensor block, the sensor block can transition from the active state backinto the inactive state in Block S112, as shown in FIG. 4 . Inparticular, if the sensor block fails to detect motion over a presetperiod of time—such as by actively sampling the motion sensor or bypassively recorded motion events output by the motion sensor—the sensorblock can selectively execute a scan cycle out of sequence; if thesensor block then fails to detect a human in the field of view of theoptical sensor during this scan cycle, the sensor block can return tothe inactive state in Block S112 since this work area is unlikely toexhibit a state change until subsequent motion is detected.

In a similar variation, once in the active state, the sensor block canexecute a sequence of scan cycles, as described above. If, during a scancycle in the sequence, the sensor block records an image in Block S120and then detects absence of humans in the second image in Block S130,the sensor block can query a local log of motion events detected by themotion sensor. Given a lack of motion events detected by the motionsensor for more than a threshold duration of time (e.g., five minutes)and concurrent failure to detect humans in the image, the sensor blockcan: transmit confirmation of vacancy in the work area in Block S150;transmit occupancy, asset, and/or work area data generated duringpreceding scan cycles and stored in a local cache to the remote computersystem in Block S150; and then transition from the active state into theinactive state in Block S112.

For example, for the sensor block installed in a conference room, thesensor block can thus determine that the conference room is vacant,offload both confirmation of vacancy in the conference room and dataextracted from images recorded during a preceding meeting in theconference room to the remote computer system (e.g., via a localgateway), and then return to the inactive state until an occupant entersthe conference room at the start of a next meeting. Concurrently, theremote computer system can update a scheduler for the conference room toreflect its current vacancy. In a similar example, for the sensor blockinstalled over desks in a work area, the sensor block can thus determinethat all desks in the work area are vacant, offload confirmation ofvacancy in the work area and data extracted from images recorded over apreceding work period to the remote computer system, and then return tothe inactive state until an occupant enters the work area at the startof a next work period (e.g., at the beginning of a work day or after alunch hour). Concurrently, the remote computer system can update amanager for the work area to reflect vacancy in the work area; a manageror security personnel may then lock the building, turn off lights in thework area, or adjust an HVAC setting accordingly.

However, the sensor block can return to the inactive state in Block S112responsive to any other event (or lack of event) detected in the fieldof view of the sensor block.

9. Conference Rooms

In one application shown in FIG. 1 , the sensor block is installed on aceiling or on a wall of a conference room, such as with a field of viewof the optical sensor intersecting a conference table, a whiteboard,and/or a monitor located in the conference room. In this application,the sensor block can transition from the inactive state into the activestate in Block S110 in response to the motion sensor detecting a motionevent in the conference room, such as a door opening, a light turningon, or one or more humans walking into the conference room. While in theactive state, the sensor block can execute a series of scan cyclesbetween low-power periods to detect human occupancy in the conferenceroom and to return measures of occupancy in the conference room to theremote computer system (e.g., via the local gateway) in Blocks S130,S132, S140, and S150.

In this application, the method S100 can further include Block S160,which recites, at the remote computer system, updating the schedulerassociated with the conference room (hereinafter the “conference roommanager”) to indicate that the conference room is occupied at the firsttime based on the first total occupancy exceeding a threshold occupancy.In Block S170 described below, the remote computer system canadditionally or alternatively: modify HVAC controls (e.g., to improveair quality or tighten controls on air temperature) when the sensorblock indicates that the conference room is occupied, and vice versa; orprompt an administrator, support staff, or maintenance staff to servicethe conference room based on meeting qualities or conference roomqualities derived and returned by the sensor block while in the activestate.

9.1 Occupation Detection

In this application, the sensor block can implement the foregoingmethods and techniques to transition from the inactive state in BlockS110, to record an image during a scan cycle in Block S120, and todetect a human in the image—and therefore occupying the conferenceroom—in Block S130. The sensor block can execute a first scan cycleimmediately upon entering the active state in Block S120. Alternatively,the sensor block can delay executing a first scan cycle for a presetdelay time (e.g., two minutes) after entering the active state, asdescribed above, which may be sufficient time for meeting attendees toaggregate in the conference room such that occupancy detected by thesensor block during this first scan cycle is more likely to represent amaximum occupancy of the conference room during the meeting. Byimplementing this delay time, the sensor block can also reduce energyconsumption for non-occupancy or non-use motion events, such as a humanreturning to the conference room to collect an item left during aprevious meeting in the conference room. Once the sensor block thusdetects and confirms occupancy of the conference room from data recordedduring this first scan cycle in Block S130 and returns confirmation ofoccupancy to the remote computer system in Block S150, the sensor blockcan then execute scan cycles on a regular (or varying) interval untiloccupancy of the conference room is not longer detected.

During the first scan cycle and during subsequent scan cycles, thesensor block can also detect human effects present in the conferenceroom and interpret clusters of human effects as intent of a human toreturn to the location of this cluster of human effects in theconference room, as shown in FIGS. 1 and 4 , even though the human maynot currently be present. For example, the sensor block can detect acomputer, a coffee cup, a coat, and a notebook, etc. in an imagerecorded during a scan cycle in Block S130 and isolate a cluster of suchhuman effects. The sensor block can then associate this cluster of humaneffects with one human occupant in Block S132, such as if this clusterof human effects: is located remotely from another human detected in theimage; is located on or immediately adjacent an empty chair detected inthe image; or if a human was detected in this chair or immediatelyadjacent these human effects during a preceding scan cycle.

In this example, the sensor block detects a first quantity of humans ina first image recorded during a first scan cycle while in the activestate in Block S130 and outputs this first quantity of humans to theremote computer system in Block S150. If the sensor block later detectsone fewer human in a second image recorded during a second, subsequentscan cycle, the sensor block can: predict that the departed humanintends to return to the conference room during the current conferenceroom meeting in Block S132 if the sensor block detects humans remainproximal the same location that the departed human was detected in thefirst image; and then preserve the first quantity as the currentoccupancy of the conference room in Block S140, even though the departedhuman was not directly detected in the second image.

However, if the sensor block fails to detect any humans in a third imagerecorded during a third, subsequent scan cycle and determines that mosthuman effects located proximal these humans have been removed from theconference room based on features extracted from a third image recordedduring a third, subsequent scan cycle, the sensor block can: predictthat any human effects remaining in the conference room were leftaccidently in the conference room; transmit both confirmation of vacancyof the conference room and a notification for a possible lost personalitem in the conference room to the remote computer system in Block S150;and then enter the inactive state in Block S112. The remote computersystem can then: serve a notification to an owner and/or to invitees ofthe last scheduled meeting in the conference room—such as stored in theconference room manager—to indicate that a personal item may have beenleft in the conference room; and note the conference room as unoccupiedin the conference room manager, as described below.

In this application, the sensor block can implement similar methods andtechniques to detect: locations of chairs; whether chairs are occupied;whiteboard use; monitor or television use; etc. in the conference roomfrom features in an image recorded during a scan cycle while in theactive state.

9.2 Occupation Quality

In one variation shown in FIGS. 1 and 4 , during each scan cycleexecuted by the sensor block while in the active state, the sensor blockcan: record an image through the optical sensor in Block S120; detecthumans in the conference room at this time based on features detected inthe second image in Block S130; and characterize engagement betweenhumans in the conference room at this time based on features detected inthe image and estimate a meeting quality in the conference room based onengagement between humans in the conference room at this time in BlockS134. In this variation, the sensor block can also transmit both thismeeting quality and occupancy of the conference room at this time to theremote computer system in Block S150.

In one example, after determining a total quantity of occupants in theconference room during a current meeting in Block S140, the sensor blockcalculates a quality of the meeting as a function of (e.g., proportionalto) this quantity of occupants. The sensor block can also calculate aquality of the current meeting as a function of peak occupant density inthe conference room, since high occupant density (i.e., occupants inclose proximity) may suggest that these occupants are more engaged andworking together. Similarly, the sensor block can also calculate ahigher quality for the current meeting if the sensor block determinesthat occupants detected in the conference room are facing each other orif a microphone integrated into the sensor block detects a higheramplitude of sound during the current scan cycle or during a recentsequence of scan cycles; and vice versa.

The sensor block can also calculate a higher quality of the meeting as afunction of types of assets used in the conference room. For example,the sensor block can: detect use of a whiteboard in the conference roombased on proximity of a human to a known location of a whiteboard in theconference room or based on density of content in a region of animage—recorded during a current scan cycle—corresponding to thewhiteboard; and then calculate a higher quality of the current meetingaccordingly. In another example, the sensor block can: calculate anasset entropy of the conference room, as described below, which mayindicate total use of assets in the conference room and thus an “energy”of the conference room; and calculate a quality of the current meetingas a function of (e.g., proportional to) this asset entropy.

In the foregoing examples, the sensor block can calculate a quality of:1/10 if only one human is detected in the conference room; 2/10 if onlyone human is detected in the conference but is active in a conference orvideo call, such as determined from sound levels in the conference roomor activity on a monitor or computer screen in the conference room; 3/10if multiple humans working independently or with minimal engagement aredetected in the conference room; and 4/10 or greater if multipleoccupants actively engaged in a meeting are detected in the conferenceroom, with greater conference room qualities calculated if the sensorblock detects use of a whiteboard, high peak occupant density, and/oractive conversation (e.g., through local sound level), etc.

However, in this application, the sensor block can derive a quality of acurrent meeting in the conference room in Block S134 in any other wayand based on any other features detected in an image recorded by thesensor block or based on data recorded through any other sensors in thesensor block.

The sensor block can then transmit this derived meeting quality to theremote computer system, such as during the current scan cycle, when thesensor block wirelessly connects to the gateway during a future scancycle, or when the meeting quality falls below a preset thresholdquality.

9.3 Asset Entropy

In this application, the sensor block can also detect changes in mobileassets in the conference room, such as from a baseline state in theconference room, during the current meeting; and calculate aquantitative or qualitative “asset entropy” value that represents thesechanges, shown in FIGS. 1 and 4 .

In one implementation, prior to a meeting in the conference room, thesensor block can: record an image of the conference room; detectlocations (and orientations) of objects in the conference room from theimage; and generate a baseline asset map for the conference room, whichmay define or indicate “ideal” or baseline types, frequencies,locations, and orientations of various assets (e.g., chairs, monitors,phones, whiteboards, trashcans, etc.) in the conference room. Forexample, the sensor block can: record a baseline image after a scheduledcleaning or maintenance of the conference room, such as at 10 PM onweekdays or 30 minutes before a scheduled meeting in the conferenceroom; then extract a baseline asset map from this baseline image. Inanother example, the sensor block can: generate an asset map fromfeatures extracted from an image recorded during a last scan cycleduring a preceding meeting in the conference room; and store this assetmap as a baseline asset map for comparison to asset maps generatedduring a next meeting in the conference room.

Later, when the sensor block executes a scan cycle while a meeting isongoing in the conference room, the sensor block can: record an image ofthe conference room; implement similar methods to extract an in-meetingasset map from this image; compare this in-meeting asset map to thebaseline asset map to identify changes in locations and/or orientationsof assets in the conference room; and then represent these changes as asingular asset entropy value for the current scan cycle within thecurrent meeting. For example, the sensor block can calculate an assetentropy proportional to use of assets in the conference room, such ashow far chairs in the conference room have moved from their baselinepositions, whether a fixed monitor in the conference room has beenactivated, and whether content has been generated on a whiteboard—all ofwhich may indicate more activity and more human engagement in theconference room.

However, the sensor block can calculate a qualitative of quantitativeasset entropy value—representing changes in the state of the conferenceroom and/or changes in the states or location of assets in theconference room in any other way.

The sensor block can repeat this process to calculate an asset entropyfor each scan cycle and can selectively transmit asset entropy values tothe conference room in Block S150, as described below.

9.4 Conference Room Scheduler Update

Upon receipt of an occupancy value from the sensor block, the remotecomputer system can update the conference room manager to reflect thisoccupancy value in Block S160, such as whether the conference room isoccupied, a quantity of occupants, and/or a quality of a current meetingongoing in the conference room. The conference room manager can then berendered on a display adjacent a door of the conference room or accessedthrough web portals or native applications executing on computingdevices accessed by employees, contractors, clients, visitors, etc. ofthe facility to view current occupancy, view upcoming reservations, andenter new reservations for the conference room (and various otherconference rooms in the facility).

In one variation, the remote computer system can update the conferenceroom manager to indicate that the conference room is occupied andunavailable (e.g., reserved, not currently bookable) if the last meetingquality received from the sensor block exceeds a threshold quality(e.g., a minimum meeting quality set by a manager of the facility or abuilding manager). However, if the second meeting quality falls belowthe threshold quality, the remote computer system can update thescheduler to indicate that the conference room as occupied but bookable,thereby enabling other occupants in the facility—who may be in need of aconference room to host a higher-quality meeting—to enter a reservationfor the conference room over the existing meeting in the conference roomand to displace current occupants from the conference room. Inparticular, if the quality of the current meeting in the conference roomfalls below the threshold quality, the remote computer system can updatethe conference room manager to reflect this low-quality meeting andenable members if the facility (e.g., employees, contractors, clients,visitors, etc.) to “bump” current occupant(s) out of the conference roomin order to make room for a higher quality meeting, such as with moreoccupants and/or more engaged occupants.

In this variation, the remote computer system can activate this optionto override a current low-quality meeting in the conference room: ifcurrent occupancy in the conference room is unscheduled; if areservation for the current meeting in the conference room was enteredwithin a threshold period of time (e.g., within the last hour); if fewerthan a threshold proportion of invitees are noted in the reservation forthe current meeting are detected by the sensor block in the conferenceroom; or if the meeting quality has remained below the threshold qualityfor at least a threshold duration (e.g., five minutes, or a durationlonger than a typical time for participants in a meeting to dispersefrom a conference room). In this variation, the remote computer systemcan additionally or alternatively limit this option to override acurrent low-quality meeting in the conference room for a replacementreservation that lists at least a threshold number of participants(e.g., at least four participants) predicted to yield or that commonlyyields a meeting quality greater than the meeting quality of the currentmeeting.

However, in this variation, the remote computer system can update theconference room manager to reflect current occupancy or current meetingoptions for the conference room in any other way based on data receivedfrom the sensor block.

9.5 HVAC Controls

In one variation shown in FIGS. 3A and 3B, the remote computer systemautomatically modifies HVAC or other facility controls in Block S170based on data received from the sensor block. In one implementation, inresponse to receipt of a total occupancy of the conference room—greaterthan null—from the sensor block, the remote computer system: tightens atolerance on a target temperature in the conference room; and serves acommand specifying a temperature change in the conference room to aventilation control system (e.g., an HVAC system) in the facility.Generally, in this implementation, the remote computer system can applya larger tolerance (i.e., a larger permitted variance, such as of +/−5°F.) for temperature in the conference room when the conference room isnot occupied, which may reduce energy consumption in the facility.However, when the remote computer system receives confirmation of anoccupant in the conference room from the sensor block, the remotecomputer system can immediately reduce the tolerance for temperature inthe conference room (e.g., to +/−1.5° F.) and serve an HVAC command todrive the conference room closer to a target temperature within thisnarrow tolerance range in Block S170, thereby rapidly and automaticallydriving the conference room to a temperature more comfortable forcurrent occupants of the conference room.

Subsequently, in response to detecting absence of humans and/or absenceof human effects in an image recorded during a current scan cycle andprior to transitioning from the active state back into the inactivestate, the sensor block can transmit confirmation of vacancy in theconference room to the remote computer system; in response to receipt ofconfirmed vacancy in the conference room from the sensor block, theremote computer system can again loosen the tolerance on the targettemperature in the conference room.

In a similar implementation, the remote computer system can: reduce thetolerance for temperature in the conference room as a function of timethat the sensor block has detected at least one occupant in theconference room during a current active state period; or once theconference room has been occupied for at least a threshold duration oftime (e.g., one minute) in order to prevent cycling HVAC controls forthe conference room when humans walk into and then quickly leave theconference room (e.g., to retrieve a personal item or to turn off amonitor in the conference room).

In another implementation, the remote computer system modifies a rate ofair exchange through the conference room as a function of occupancy. Forexample, the sensor block can serve a quantity of humans in theconference room to the remote computer system each time the sensor blockdetermines that a quantity of humans in the conference room has changed.In response to receiving a quantity of humans in the conference roomfrom the sensor block in Block S150, the remote computer system can:calculate a target rate of air exchange in the conference roomproportional to the quantity of humans in the conference room; and thenserve a command specifying the target rate of air exchange to aventilation control system connected to the conference room in BlockS170. The sensor block and the remote computer system can thereforecooperate to automatically adjust a rate of air exchange in conferenceroom as a function of number of occupants, including: increasing rate ofair exchange in the conference room as occupancy increases in order tocompensate for greater thermal output and respiration by these occupantsand thus maintain a hospitable environment for occupants in theconference room; and reducing or stopping air exchange in the conferenceroom when occupants leave the conference room in order to reduce energyconsumption in the facility when the conference room is not occupied.

In this variation, the sensor block and the remote computer system canalso cooperate to adjust latency of HVAC control output by the remotecomputer system based on various room characteristics. For example,during a setup period for the sensor block installed on a ceiling in theconference room, the processor can determine that sensor block islocated on a ceiling based on an output of the orientation sensorintegrated into the sensor block. The processor can then: sample a 1Ddepth sensor integrated into the sensor block to determine a distancefrom the sensor block to the opposing floor; record an image through theoptical sensor; detect types of assets in the image, as described above;and then determine whether the sensor block is placed over a floor orover a table (i.e., whether the floor or a table is in the field of viewof the depth sensor) based on whether a table is present in the centerof the image. If no table is detected at the center of the image (orotherwise in the field of view of the depth sensor) and the processorthus determines that the sensor block is arranged over a floor, theprocessor can store the depth value as the height of the conferenceroom. Otherwise, the processor can add a standard table height (e.g.,30″) to the depth value and store this sum as the height of theconference room. The processor can then: detect a perimeter of theconference room in the image; extract a non-dimensional length and widthof the room from the color image; transform the non-dimensional lengthand width values into a dimensioned length and width of the conferenceroom based on known properties of the optical sensor and the height ofthe conference room; and then store a product of the length, width, andheight of the conference room as a volume of the conference room.

The processor can implement similar methods and techniques to determinethat the sensor block is installed on a wall of the conference room, tostore an output of the depth sensor as a depth of the room, to extract aheight and width of the room from an image recorded by the opticalsensor, and to calculate a volume of the conference room accordingly.

The sensor block can then return this volume estimate of the conferenceroom to the remote computer system; and the remote computer system canexecute, generate, and serve HVAC controls more rapidly for conferencerooms with smaller volumes in order to compensate for faster temperatureand air quality changes when humans are present. The sensor block canadditionally or alternatively set a time interval between scancycles—executed by the sensor block in the active state—proportional toa volume of the room occupied by the sensor block, thereby enabling thesensor block to detect occupancy changes and to communicate thesechanges to the remote computer system more rapidly for smallerconference rooms, since ambient conditions in these smaller conferencerooms may be affected more quickly by individual human occupants thanambient conditions in larger spaces in the facility.

However, the remote computer system can serve commands to the HVACsystem or other controls in the facility in any other way in Block S170in order to control an environment within the conference room responsiveto any other data output by the sensor block in Block S150.

9.6 Data Offload

In one variation shown in FIG. 4 , the sensor block can selectivelyreturn data to the remote computer system, such as via a local gateway,in Block S150. In particular, wireless transmission of data may beassociated with relatively high energy cost and reduced battery life,such as compared to recording and processing images in Block S120, S130,and S132. The sensor block can therefore, selectively and intelligentlyoffload data to the local gateway in Block S150 in order to extendbattery life of the sensor block.

In one implementation, the sensor block executes a first scancycle—including recording a first image at a first time—after enteringthe active state in Block S110 and transmits occupancy data for theconference room to the remote computer system—such as via thegateway—upon concluding the first scan cycle. While in the active state,the sensor block then executes a series of scan cycles between periodsof low-power operation following the first scan cycle, as describedabove. During each scan cycle in this series of scan cycles, the sensorblock can: record an image through the optical sensor in Block S120;detect a quantity of humans in the conference room based on featuresdetected in this image in Blocks S130 and S132; and store these quantitydata in a local cache. Throughout this active state period, the sensorblock can also: record a last time that an output of the motion sensorindicated motion in the conference room; and execute a second scancycle—including recording a second image through the optical sensor andscanning the second image for humans and human effects—out of order ifthe last time that the motion sensor detected motion precedes a currenttime by more than a threshold duration (e.g., five minutes). If thesensor block then detects absence of humans and absence of human effectsindicative of human occupancy in the conference room in the secondimage, the sensor block can: transmit a time series of occupancy datafor the conference room following the first time to approximately thecurrent time—stored in the cache—to the local gateway in Block S150; andthen transition from the active state into the inactive state in BlockS112, as described above. At the conclusion of this active state period,the sensor block can additionally or alternatively: calculate a peakoccupancy, an average occupancy, an occupancy variance, an activitylevel, a level of occupant engagement, assets engaged (e.g., chairs,monitors, or whiteboards used), an asset entropy, and/or a meetingquality, etc. for the meeting that just ended in the conference room;and then return these metrics to the remote computer system, such as viathe gateway. The sensor block can therefore selectively connect andoffload data to the gateway at the beginning and conclusion of an activestate period, thereby enabling the remote computer system to respond tovacant and occupied states of the conference room, such as by updatingthe conference room manager in (near) real-time when the conference roomtransitions from vacant to occupied and vice versa.

In one example, the sensor block executes a first scan cycle uponentering the active state—including recording a first image at a firsttime and detecting a first distribution of objects in a first imagerecorded during this first scan cycle. During a second scan cycle at theconclusion of the current active state period, the sensor block: recordsa second image at a second time; detects a second distribution ofobjects in the second image; calculates an object entropy in the workarea based on a difference between the first distribution of objects andthe second distribution of objects; and then transmits the objectentropy to the remote computer system. In response to receipt of thisobject entropy that exceeds a threshold entropy—which may correlate todisorder in the conference room—the remote computer system serves aprompt to straighten or clean the conference room to maintenance staffin the facility at approximately the second time, thereby enablingmaintenance staff to quickly and judiciously focus efforts to tidyingthe conference room rather than other spaces exhibiting less deviationfrom a baseline (e.g., less entropy).

In another implementation, the sensor block transmits confirmation thatthe conference room is occupied to the remote computer system when atleast one occupant has occupied the conference room for a thresholdperiod of time (e.g., two minutes). For example, the sensor block can:execute a first scan cycle immediately upon entering the active statewhen the motion sensor detects motion in the conference room in order toconfirm initial presence of an occupant in the conference room; executea second scan cycle two minutes later to confirm that the conferenceroom is still occupied; transmit confirmation of occupancy of theconference room to the local gateway in Block S150 only if the occupancyis detected during both the first and second scan cycles; resumeexecuting scan cycles on a five-minute interval if such occupancy isdetected; and otherwise return to the inactive state in Block S112.

The sensor block can additionally or alternatively transmit data to thegateway (or directly to the remote computer system) intermittentlybetween the beginning and end of the current active state period. In oneexample, the sensor block regularly executes scan cycles and determinesa quantity of occupants in the conference room during each scan cycle,as described above. During a current scan cycle, in response to thecurrent quantity of humans in the conference room calculated by thesensor block differing from a quantity of humans detected in theconference room during a preceding scan cycle, the sensor block cantransmit the current quantity of humans detected in the conference roomto the remote computer system; otherwise, the sensor block can writevarious data extracted from the current image to the cache and return tothe low-power mode before a next scan cycle. In the variation describedabove in which the sensor block and the remote computer system cooperateto serve HVAC commands to modify air quality in the conference roombased on conference room occupancy, the sensor block can thus returnoccupancy data—in near real-time—to the remote computer system each timethat a quantity of humans detected in the conference room changes (i.e.,increases or decreases) while the conference room is occupied by asleast one human. The remote computer system can then leverage these datato issue commands to ventilation control system within the facility inorder to modify air quality (e.g., air temperature, rate of airexchange) in the conference room in (near) real-time as occupancy in theconference room changes.

In a similar implementation, the sensor block can selectively transmitoccupancy data to the remote computer system if the sensor block detectsoccupancy in the conference room that exceeds a threshold quantity or athreshold proportion of seats allocated for the conference room. Forexample, if the sensor block detects occupancy that exceeds a presetoccupancy threshold set for the conference room, the sensor block canimmediately send these occupancy data to the remote computer system. Theremote computer system can then: dispatch support staff to providerefreshments, confirm sufficient seating, provide technical assistance(e.g., for connecting to A/V equipment in the conference room), and/orconfirm availability of presentation materials (e.g., whiteboard markersand erasers) in the conference room. The sensor block and the remotecomputer system can thus selectively prompt support staff to offergreater assistance in conference rooms that exhibit certaincharacteristics indicative of high-quality meetings.

The sensor block can additionally or alternatively selectively transmitoccupancy data for the conference room to the remote computer system ifa meeting quality derived from an image recorded by the sensor blockduring a current scan cycle falls below a preset threshold (e.g., 3/10or less). Upon receipt of these data from the sensor block, the remotecomputer system can update the conference room manager to reflect thislower-quality meeting, such as by enabling other employees, contractors,clients, visitors, etc. of the facility to “bump” current occupants outof the conference room, as described above.

Alternatively, the sensor block can transmit occupancy, environmental,meeting quality, asset entropy, and/or other data collected or derivedduring a current scan cycle to the remote computer system (e.g., via thelocal gateway) prior to the conclusion of the current scan cycle. In theexample above in which the sensor block executed scan cycles on aten-minute interval, the sensor block can thus connect to and uploadconference room occupancy data, etc. to the gateway once per ten-minuteinterval following first confirmed occupancy of the conference roomduring a current meeting and up to a limited period of time after exitof a last occupant from the conference room.

However, the sensor block can selectively offload data of any other typeand responsive to any other condition detected in the conference room inBlock S150.

10. Agile Work Environment

In another application shown in FIGS. 3A and 3B, the sensor block isinstalled on a ceiling or on a wall adjacent an agile work environmentcontaining a set of non-dedicated work surfaces, such as desks, tables,or workstations (hereinafter “agile desks”) that are not reservable orthat are reservable for limited durations of time, such as for one hour,one day, or for one week. In particular, in this application, the sensorblock can be arranged within the facility with the motion sensor and theoptical sensor defining fields of view intersecting all or a portion ofthe agile work environment. The sensor block can thus transition fromthe inactive state into the active state in response to the motionsensor detecting a motion event in the agile work environment in BlockS110. During a scan cycle, the sensor block can then: record an imagethrough the optical sensor defining a field of view occupied by a set ofagile desks in Block S120; interpret proximity of a first set of humansto locations of a first subset of these agile desks—detected in theimage—as occupancy of the first subset of agile desks (hereinafter“present occupancy”) in Block S130; and interpret proximity of a secondset of human effects (e.g., clothing, bags, coffee cups, notebooks,laptop computers) to locations of a second subset of agile desks andabsence of humans proximal the second subset of agile desks—detected inthe image—as human-not-present occupancy (hereinafter “absentoccupancy”) of the second subset of agile desks.

The sensor block can therefore locally implement a contextual model toextract contextual understanding of present and absent occupancy of adesk from both human and non-human features detected near this desk inan image recorded by the sensor block during a scan cycle; the sensorblock can then return these occupancy data to the remote computer systemin Block S150. The remote computer system can then update a schedulerassociated with the set of agile desks (hereinafter an “agile deskmanager”) in (near) real-time to indicate that the first and secondsubsets of agile desks are occupied based on occupancy data receivedfrom the sensor block. Employees, contractors, clients, and/or visitors,etc. of the facility may then access this agile desk manager—such asthrough a web browser or native application executing on a personalcomputing device or through a user interface rendered on a display nearthe agile work environment—to view and reserve available desks.

In one implementation, a remote computer system can: populate a virtualrepresentation of the agile work environment with representations ofdesks in the agile work environment and these desk's last-detectedoccupancy states; and update a graphical user interface within the agiledesk manager rendered on a display. Therefore, the agile desk managercan render desk representations marked by distinct graphicalrepresentations of each occupancy state in the group of occupancy states(including “occupied with human present,” “occupied with human absent,”and “vacant”). The agile desk manager can render a map indicatingrelative locations of each desk in the agile work environment and rendera representation of each desk indicating the occupancy state associatedwith that desk. In one example, the agile desk manager can represent:that a desk is occupied with a human present via a first graphicalrepresentation associated with the “occupied with human present”occupancy state (e.g., a red color of the graphical representation ofthe desk); that the desk is occupied with a human absent via a secondgraphical representation associated with the “occupied with humanabsent” occupancy state (e.g., an orange color of the graphicalrepresentation of the desk); and that the desk is vacant via a thirdgraphical representation associated with the “vacant” occupancy state(e.g., a green color of the graphical representation of the desk). Thus,the agile desk manager can distinguish each occupancy state of a desk ina user interface representing the agile desk environment.

10.1 Desk Locations and Types

In one implementation, the sensor block implements methods andtechniques described above to detect desks in the field of view of theoptical sensor during a setup period, automatically generates a “deskmap” representing locations and orientations of desks detected in thefield of view of the sensor block, and uploads the desk map to theremote computer system, such as via the gateway. Other sensor blocks inthe agile work environment can implement similar methods and techniquesto return desk maps representing locations of desks in other discrete oroverlapping areas of the agile work environment. The remote computersystem can then aggregate desk maps—received from this population ofsensor blocks arranged throughout the agile work environment—and compilethese desk maps into a “global desk map” representing positions andorientations of desks throughout the agile work environment based onknown positions and orientations of these sensor blocks throughout theagile work environment.

In this implementation, the remote computer system can then serve thisdesk map to an administrator affiliated with the agile workenvironment—such as through an administrator portal accessible through aweb browser or native application—and then prompt the administrator tomanually label types of work areas or types of specific desks in thisglobal desk map. For example, the remote computer system can prompt theadministrator to label each desk, cluster of desks, or region in theagile work environment as one of: dedicated (i.e., permanently assignedto employees); agile and bookable (i.e., non-dedicated but bookable byemployees, etc. for limited periods of time according to defined rules);or agile and non-bookable (i.e., non-dedicated and not bookable). Theremote computer system can then generate an agile desk manager orselectively apply predefined rules for desks in the agile workenvironment based on desk type labels provided by the administrator.

Alternatively, the remote computer system can access an existing floorplan of the agile work environment; extract a global desk map from thisfloor plan, such as by implementing computer vision techniques;interface with an administrator of the agile work environment to labeldesk types in this global desk map, such as described above; and thenport desk type labels from this global desk map onto desk maps generatedby sensor blocks throughout the agile work environment based on knownpositions and orientations of these sensor blocks within the agile workenvironment.

Yet alternatively, the remote computer system can serve an imagerecorded by a sensor block during a setup period to an administratorportal and prompt the administrator to label locations and types ofdesks in this image within the administrator portal. For example, theadministrator can draw a desk boundary around the perimeter of each deskin the image or around the desk and a floor area around the desk andlabel each of these desk boundaries with a type of desk containedtherein. The remote robotic system can then return these desk boundariesto the sensor block, and the sensor block can implement these desklocations, boundaries, and types to monitor occupancy of agile desks inBlocks S130 and S132.

However, a sensor block and the remote computer system can cooperate inany other way to access or generate a global desk map labeled withlocations and types of agile desks throughout the agile workenvironment.

10.2 Agile Desk Rules

The remote computer system can also access rules for agile desks in theagile work environment, such as: a maximum duration over which an agilemay be reserved by one user before the reservation is cleared and theagile desk noted as available in the agile desk manager; a maximumduration that an agile desk may be occupied while a human is not presentbefore the agile desk is noted as available in the agile desk manager;and/or a maximum duration of time that a reservation for an agile deskis held for a user while the agile desk remains unoccupied before thereservation is cleared.

In one implementation, the remote computer system prompts theadministrator to manually define these rules or to selectively linkthese rules to agile desks throughout the agile work environment, suchas through an administrator portal. Alternatively, the remote computersystem can extract these rules from an existing agile desk manager forthe facility.

10.3 Human Occupancy

As described above, a sensor block can remain in the inactive state bydefault and then transition into the active state when an output of themotion sensor indicates motion within the field of view of the sensorblock. While in the active state, the sensor block can execute scancycles on a regular interval, such as once per ten-minute interval,between low-power periods.

10.3.1 Human Occupancy with Human Present

After recording an image during a scan cycle in Block S120, the sensorblock can implement methods and techniques described above to detecthumans, mobile assets (e.g., chairs, laptop computers), human effects(e.g., coffee mugs, bags, clothing), and fixed assets (e.g., desks) inthe image in Blocks S130 and S132. The sensor block can additionally oralternatively leverage predefined locations or boundaries of desks—inthe field of view of the optical sensor—received from the remotecomputer system, as described above, to isolate desks in the image. Thesensor block can then selectively associate humans and/or objectsdetected in the image with certain desks in the agile work environment.

In one implementation, the sensor block implements artificialintelligence and computer vision techniques described above or leveragesdesk locations or desk boundaries received from the remote computersystem (e.g., extracted from a floor plan of the facility by the remotecomputer system or manually labeled by an administrator) as describedabove to isolate a set of desks in the image. Upon detecting a firsthuman in the image, the sensor block can associate this human with afirst agile desk detected in the image if the first human is occupying achair, is facing the front of the first agile desk, and falls within afirst threshold distance (e.g., one meter) of the first agile desk; andmark first desk as occupied in Block S130. The sensor block can alsoassociate a second human with a second agile desk—both detected in theimage—if the second human is standing at the front of the second deskand is within a second threshold distance less than the first thresholddistance (e.g., one-half meter) of the second desk in Block S130.

In Block S130, the sensor block can alternatively calculate aprobability that a human is occupying a desk based on similar featuresdetected in the image. For example, the sensor block can calculategreater probability that a human is occupying a desk if the human isseated in a chair, if the human is facing the front of the desk, and ifthe human's hands are located over the desk (e.g., over a notepad,computer, or keyboard also detected on the desk). The sensor block canalso calculate this probability as an inverse function of a distancefrom the human to the desk and proportional to a number of contiguousscan cycles over which the sensor block determined that the desk wasoccupied.

10.3.2 Human Occupancy with Human Not Present

In the foregoing implementation, upon detecting a cluster of humaneffects and/or mobile assets (e.g., a bag, a coat, a laptop computer,and/or a coffee mug) in the image, the sensor block can also: group asubset of objects arranged on or near a third desk in the image into acluster of objects; and then associate this cluster of objects withoccupation of the third desk by a third human even though the thirdhuman was not present at the third desk at the time the sensor blockrecorded the image, as shown in FIG. 3B. For example, in Block S132, thesensor block can: detect computing devices, clothing, notebooks, anddrink containers, etc. in the image; and group human effects in thefirst image into a set of clusters of human effects based on proximityto one another or proximity to locations (e.g., centroids) or boundariesof nearby desks. The sensor block can then associate a particularcluster of human effects with a particular agile desk, such as if humaneffects in this particular cluster: intersect the particular agile deskdetected in the image; fall within a boundary (e.g., extracted from theimage or predefined and stored in memory on the sensor block) of theparticular desk; or fall within a threshold distance of a centroid(e.g., extracted from the image or predefined and stored in memory onthe sensor block) of the particular desk. Finally, the sensor block canpredict absent occupancy of the particular agile desk based on theparticular cluster of human effects and absence of a human—detected inthe first image—within a threshold distance of the particular agile deskor within the predefined boundary around the particular desk in BlockS132. For example, if this cluster of human effects falls within theboundary of the particular desk and includes a sufficient number,certain types, or a particular combination of human effects known toexhibit a high likelihood of human occupancy, the sensor block caninterpret these human effects as occupancy of the particular desk inBlock S132 regardless of whether a human is detected sitting or standingnear the particular desk.

Alternatively, the sensor block can calculate a probability that theparticular desk is occupied. For example, the sensor block can store alookup table for values of human indicators for various types of humaneffects and mobile assets. Upon recording an image and detecting humaneffects and mobile assets in this image in Blocks S120 and S132, thesensor block can: calculate a distance from the centroid of each ofthese objects to a centroid of a desk in the image; weight the humanindicator value for each of these objects based on distance (e.g., asquare of the distance) from the centroid of the desk; and sum orcompile these weighted human indicator values to calculate a probabilitythat the desk is occupied in Block S132. The sensor block can thenpredict that a human is occupying but not present at the particular deskif this probability exceeds a preset threshold.

Yet alternatively, the sensor block can implement artificialintelligence techniques to transform the image into occupancy states orprobabilities of occupancy at a desk represented in the image.

However, the sensor block can implement any other methods or techniquesto interpret presence of human effects, mobile assets, etc. intooccupancy of a nearby desk. The sensor block can repeat these methodsand techniques for each other desk represented in the image recordedduring the current scan cycle, and the sensor block can repeat thisprocess during each subsequent scan cycle during the current activestate period.

10.3.3 Desk Vacancy

Furthermore, during a scan cycle, the sensor block can interpret absenceof humans and absence of human effects—detected in the image—proximalthe location of a particular agile desk as vacancy of the particularagile desk. For example, if the sensor block detects no human within athreshold distance of the particular desk, if the sensor block detectsfewer than a threshold number or type of human effects within a boundaryof the particular desk, or if the sensor block calculates a probabilityof human occupation less than the preset threshold described above, thesensor block can determine that the particular desk is vacant.

10.4 Occupancy Data Format

In preparation to offload desk occupancy data to the remote computersystem in Block S150, the sensor block can compile occupancy states ofdesks in its field of view into a format readable by the remote computersystem (or by the agile desk manager). In one implementation shown inFIGS. 3A and 3B, the sensor block generates a list or matrix of desklocations of each desk detected in an image recorded by the sensor blockduring the current scan cycle, such as with each desk delineated by thelatitude and longitude of its centroid in a local coordinate systemimplemented by the sensor block. The sensor block then writes theoccupancy of each desk—determined by the sensor block during the currentscan cycle—to its corresponding cell in the list or matrix, such as avalue for one of “occupied with human present,” “occupied with humanabsent,” or “vacant.”

Upon receipt of this list or matrix from the sensor block, the remotecomputer system can then: transform each desk location—in this list ormatrix—in the sensor block coordinate system in a desk location in aglobal coordinate system for the agile work environment or for thefacility more generally based on a known position and orientation of thesensor block in the agile work environment; and match each of thesecorrected desk locations to a known desk in the agile work environment,such as to associate each desk location indicated in this list or matrixreceived from the sensor block with an unique identifier of one agiledesk in the agile work environment.

For example, the sensor block can transmit, to the remote computersystem: confirmation of present occupancy of a first subset of agiledesks; confirmation of absent occupancy of a second subset of agiledesks; confirmation of vacancy of a third subset of agile desks; andlocations of the first, second, and third subsets of agile desks in thefield of view of the optical sensor to the remote computer system at theconclusion of a scan cycle in Block S150.

Alternatively, in this implementation described above in which theremote computer system returns a desk map or desk boundaries for agiledesks in the field of view of the optical sensor to the sensor block,the remote computer system can also return a unique identifier for eachof these desk locations or desk boundaries to the sensor block. In thisimplementation, the sensor block can thus return a unique identifier andan occupancy state for each desk in its field of view to the remotecomputer system to conclude a scan cycle in Block S150.

In the foregoing implementation, the remote computer system can then:reference locations of these agile desks to a map of known agile desklocations in the agile work environment to determine a unique identifierof each of these agile desks; and update the agile desk manager toreflect these current occupancy states based on these unique identifiersin Block S160.

However, the sensor block can package the desk occupancy data in anyother format prior to offloading these data to the remote computersystem.

10.5 Data Offload

The sensor block can implement the foregoing processes to determineoccupancies of desks in its field of view and to return theseoccupancies to the remote computer system during a scan cycle. Forexample, the sensor block can return occupancy states of desks in itsfield of view at the conclusion of each scan cycle.

Alternately, the sensor block can selectively upload data to the remotecomputer system, such as only when an occupancy state of at least onedesk in its field of view has changed since a preceding scan cycle. Forexample, the sensor block can selectively upload data to the remotecomputer system when the sensor block determines that an occupant hasleft a previously-occupied desk or when an occupant is detected at apreviously-vacant desk. In a similar example, during a scan cycle, thesensor block can: calculate a distribution of occupancy and vacancy ofagile desks in the agile work environment; and then transmit the currentdistribution of occupancy and vacancy of these agile desks to the remotecomputer system if the current distribution of desk occupancy andvacancy differs from a distribution of desk occupancy and vacancydetected during the preceding scan cycle. The remote computer system canthen automatically update the agile desk manager to reflect this changein (near) real-time (e.g., within seconds) of the sensor block returningthese data.

In another implementation, the sensor block can store a local copy ofpredefined rules for desks in the agile work environment and can pushdesk occupancy data to the remote computer system when the sensor blockdetermines that one of these rules has been violated. For example, thesepredefined rules can specify a maximum time limit of eight hours foroccupation of an agile desk. In this example, if the sensor blockdetects the same human, the same combination of human effects, and/orthe same mobile asset(s) at one agile desk in its field of view over aseries of scan cycles over an eight-hour period, the sensor block can:connect to the local gateway; wirelessly transmit desk occupancydata—including a flag for time overage at this agile desk—to the localgateway; and then return to the low-power mode. Upon receipt of thesedata, the remote computer system can: notify an administrator of thistime overage (e.g., by generating and transmitting an email or otherelectronic notification to the administrator's computer or smartphone);and/or update the agile desk manager to reflect this time overage, suchas to enable another employee to reserve this desk.

In a similar example, these predefined rules can specify a maximum timelimit of two hours for occupation of an agile desk while a human is notpresent. In this example, if the sensor block detects objects (e.g.,human effects and/or mobile assets) that suggest occupancy at one agiledesk but fails to detect a human occupying this agile desk (e.g., withina threshold distance of the agile desk) during a series of scan cycleswithin a two-hour period, the sensor block can: connect to the localgateway; wirelessly transmit desk occupancy data—including a flag forabandonment of this agile desk—to the local gateway; and then return tothe low-power mode. If other agile desks in the agile work environmentare at or near capacity (e.g., more than 85% of these agile desks areoccupied) at this time, the remote computer system can then: serve aprompt to the administrator of the agile work environment to collect andstore human effects remaining at this agile desk, such as in alost-and-found bin; and update the agile desk manager to indicate thatthis agile desk is available.

Alternatively, in the foregoing implementation, the sensor block canpush desk occupancy and/or other relevant data for the agile workenvironment to the remote computer system on a regular interval, such asat the conclusion of every scan cycle or every other scan cycle; and theremote computer system can remotely apply rules to these data toselectively inform an administrator of an agile desk rule violationand/or to automatically update the agile desk manager to reflect achange in desk availability responsive to such a rule violation. Thesensor block and the remote computer system can thus cooperate tocollect and leverage agile desk occupancy data to automatically reopendesks that may have been abandoned and/or at which human effects ormobile assets may have been forgotten, thereby improving efficiency ofagile desks throughout the agile work environment.

The remote computer system can also selectively pull data from a sensorblock. For example, a particular employee may reserve an agile desk inthe agile work environment through the agile desk manager, such as by:logging in to the agile desk manager through a web browser or nativeapplication executing on her smartphone or laptop computer; selecting atime window (e.g., hours or days up to a reservation time limit) for anagile desk reservation; selecting a particular agile desk that isavailable for reservation during this time window; and then confirming areservation of this particular agile desk. In this example, the remotecomputer system can also store a rule that employees occupy theirreserved agile desks within one hour of the start of their reservationsin the agile work environment. To apply this rule, the remote computersystem can reference a global desk map of the agile work environment toidentify a particular sensor block defining a field of view thatcontains the particular agile desk reserved by the particular employee.If the particular sensor block failed to indicate that the particulardesk is occupied since the start time of the particular employee'sreservation (e.g., over five scan cycles since the start time of thereservation) and the one-hour delay period since the start of thisreservation has expired, the remote computer system can push a requestto the particular sensor block for a state of desks in its field ofview. Upon receipt of this request from the remote computer system(e.g., via the gateway), the particular sensor block can execute a scancycle and return desk occupancy data for desks in its field of view tothe remote computer system in (near) real-time. If these data returnedby the particular sensor block at the end of the one-hour delay periodof the reservation indicate that the particular agile desk reserved bythe particular employee is now occupied, the remote computer system canpreserve this reservation in the agile desk manager. However, if thesedata returned by the particular sensor block indicate that theparticular agile desk is still not occupied, the remote computer systemcan clear this reservation from the agile desk manager and note theparticular agile desk as now available in the agile desk manager.

However, the sensor block can push data to the remote computer systemand/or the remote computer system can pull data from the sensor blockresponsive to any other event in Block S150. The remote computer systemcan then update the agile desk manager to reflect occupancy and vacancyof the agile desks in the agile wireless network based on these datareturned by the sensor block.

In this variation, the remote computer system can also implement methodsand techniques similar to those described above to selectively controlHVAC, lighting, and/or other facility controls in Block S170 based ondata received from the sensor block in the agile work environment.

11. Other Work Areas

Sensor blocks distributed throughout other regions of the facility—suchas in a cafeteria, a lobby or reception area, a lounge, a hallway, aparking lot, and/or a courtyard—can implement similar methods andtechniques to transition between the inactive and active states, toexecute scan cycles while in the active state, and to selectivelyoffload occupancy and related data to the remote computer system. Theremote computer system can then implement methods and techniques similarto those described above to modify a rate of air exchange, to modify airtemperature, or to modify lighting, etc. within these areas of thefacility based on occupancy data returned by nearby sensor blocks.

The remote computer system can thus implement the foregoing methods andtechniques to update schedulers in Block S160 and/or to serve commandsto various actuators in the facility in Block S170 based on occupancydata received from many sensor blocks throughout the facility over time.For example, the remote computer system can: merge occupancy data lastreceived from these many distributed sensor blocks into a globaloccupancy map representing approximate occupancy of the facility at thecurrent time; and then selectively update schedulers, serve commands tovarious actuators, and/or serve prompts to an administrator to directher attention to particular areas of the facility based on the globaloccupancy map.

12. Scan Cycle Frequency

As described above, a sensor block can regularly execute scan cycleswhile in the active state, such as in fixed, ten-minute intervals.Alternatively, the sensor block can implement a time interval—betweenscan cycles—of duration based on a type of space that the sensor blockoccupies. For example, the remote computer system can assign a shortesttime interval to sensor blocks installed in spaces used least (i.e.,characterized by the longest durations of vacancy) or characterized bygreatest rates of occupancy change. In this example, the remote computersystem can assign: a five-minute interval to a sensor block installed ina conference room; a ten-minute interval to a sensor block installed ina cafeteria or kitchen; a twenty-minute interval to a sensor blockinstalled in an agile work environment containing many agile desks; anda thirty-minute interval to a sensor block installed in a workenvironment containing dedicated desks.

In another implementation, a sensor block can dynamically modify thetime interval it implements between consecutive scan cycles (i.e., theduration of low-power periods between consecutive scan cycles while inthe active state) as an inverse function of a rate of change of totaloccupancy that the sensor block has detected in its field of view overpreceding scan cycles.

However, the sensor block and/or the remote computer system can set ormodify this time interval for the sensor block based on any othercharacteristic of the sensor block or a space in which the sensor blockis installed.

The systems and methods described herein can be embodied and/orimplemented at least in part as a machine configured to receive acomputer-readable medium storing computer-readable instructions. Theinstructions can be executed by computer-executable componentsintegrated with the application, applet, host, server, network, website,communication service, communication interface,hardware/firmware/software elements of a user computer or mobile device,wristband, smartphone, or any suitable combination thereof. Othersystems and methods of the embodiment can be embodied and/or implementedat least in part as a machine configured to receive a computer-readablemedium storing computer-readable instructions. The instructions can beexecuted by computer-executable components integrated bycomputer-executable components integrated with apparatuses and networksof the type described above. The computer-readable medium can be storedon any suitable computer readable media such as RAMs, ROMs, flashmemory, EEPROMs, optical devices (CD or DVD), hard drives, floppydrives, or any suitable device. The computer-executable component can bea processor but any suitable dedicated hardware device can(alternatively or additionally) execute the instructions.

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the embodiments of the invention without departing fromthe scope of this invention as defined in the following claims.

We claim:
 1. A method for monitoring occupancy comprising: accessing aset of definitions of an occupied state for a desk-type assetcomprising: a first definition of an occupied with human present statefor the desk-type asset; and a second definition of an occupied withhuman absent state for the desk-type asset; accessing a third definitionof a vacant state for the desk-type asset; at a first time, recording afirst image at a sensor block, the first image depicting: a first deskcomprising the desk-type asset; and a second desk comprising thedesk-type asset; extracting a first set of features associated with thefirst desk from the first image, the first set of features representinga set of human effects, the set of human effects comprising personalobjects carried by humans in a work environment and excluding fixedassets defined by an administrator; detecting a first human effect inthe set of human effects and absence of humans within a predefined areaassociated with the first desk from the first image based on the firstset of features; in response to detecting the first human effect in theset of human effects and absence of humans within the predefined areaassociated with the first desk from the first image, identifying thefirst desk in the occupied with human absent state according to thesecond definition of the occupied state; extracting a second set offeatures associated with the second desk from the first image;identifying the second desk in the vacant state based on the second setof features and the third definition of the vacant state; and updating ascheduler to indicate the first desk in the occupied with human absentstate and to indicate the second desk in the vacant state.
 2. The methodof claim 1, wherein identifying the second desk in the vacant statebased on the second set of features and the third definition of thevacant state comprises: detecting absence of humans in the second set offeatures; and in response to detecting absence of humans in the secondset of features, identifying the second desk in the vacant stateaccording to the third definition of the vacant state.
 3. The method ofclaim 1, further comprising: at a second time, recording a second imageat the sensor block, the second image depicting a third desk comprisingthe desk-type asset; extracting a third set of features associated withthe third desk from the second image; detecting presence of a humanwithin a predefined area associated with the third desk based on thethird set of features; in response to detecting presence of the humanwithin the predefined area associated with the third desk, identifyingthe third desk in the occupied with human present state according to thesecond definition of the occupied state; and updating the scheduler toindicate the third desk in the occupied with human present state.
 4. Themethod of claim 3, wherein extracting the third set of features,associated with the third desk, from the second image comprisesextracting the third set of features of a human in the predefined areaassociated with the third desk.
 5. The method of claim 1, whereindetecting the first human effect in the set of human effects comprisesdetecting the first human effect within a threshold distance of acentroid of the first desk from the first image based on the first setof features.
 6. A method for monitoring occupancy comprising: accessinga first definition of an occupied with human absent state for adesk-type asset; accessing a second definition of a vacant state for thedesk-type asset; accessing a third definition of an occupied with humanpresent state for the desk-type asset; at a first time: recording afirst image at a sensor block, the first image depicting a first deskcomprising the desk-type asset; extracting a first set of featuresassociated with the first desk from the first image, the first set offeatures representing a set of human effects, the set of human effectscomprising personal objects carried by humans in a work environment andexcluding fixed assets defined by an administrator of the workenvironment; and identifying the first desk in the occupied with humanabsent state based on the first set of features and the first definitionof the occupied with human absent state; and at a second time: recordinga second image at the sensor block, the second image depicting a seconddesk comprising the desk-type asset; extracting a second set of featuresassociated with the second desk from the second image; and identifyingthe second desk in the occupied with human present state based on thesecond set of features and the third definition of the occupied withhuman present state; and updating a desk manager to indicate the firstdesk in the occupied with human absent state and to indicate the seconddesk in the occupied with human present state.
 7. The method of claim 6:wherein recording the first image at the sensor block comprisesrecording a first color image at the sensor block, the first color imagedepicting the first desk; and wherein recording the second image at thesensor block comprises recording a second color image at the sensorblock, the second color image depicting the second desk.
 8. The methodof claim 6: wherein recording the first image at the sensor blockcomprises recording a first depth image at the sensor block, the firstdepth image depicting the first desk; and wherein recording the secondimage at the sensor block comprises recording a second depth image atthe sensor block, the second depth image depicting the second desk.
 9. Amethod for monitoring occupancy comprising: accessing a first definitionof an occupied with human absent state for a desk-type asset; accessinga second definition of a vacant state for the desk-type asset; accessinga third definition of an occupied with human present state for thedesk-type asset; at a first time: recording a first image at a sensorblock, the first image depicting a first desk comprising the desk-typeasset; extracting a first set of features associated with the first deskfrom the first image, the first set of features representing a first setof human effects, the set of human effects comprising personal objectscarried by humans in a work environment and excluding fixed assetswithin the work environment; and identifying the first desk in theoccupied with human absent state based on the first set of features andthe first definition of the occupied with human absent state; at asecond time: recording a second image at the sensor block, the secondimage depicting a second desk comprising the desk-type asset; extractinga second set of features associated with the second desk from the secondimage; and identifying the second desk in the vacant state based on thesecond set of features and the second definition of the vacant state; ata third time: recording a third image at the sensor block, the thirdimage depicting a third desk comprising the desk-type asset; extractinga third set of features associated with the third desk from the thirdimage; and identifying the third desk in the occupied with human presentstate based on the third set of features and the third definition of theoccupied with human present state; and transmitting the occupied withhuman absent state of the first desk, the vacant state of the seconddesk, and the occupied with human present state of the third desk to aremote computer system.
 10. The method of claim 9, wherein extractingthe third set of features associated with the third desk from the thirdimage comprises extracting the third set of features of a human in apredefined area associated with the third desk.
 11. The method of claim9, further comprising, at the remote computer system: receiving theoccupied with human absent state of the first desk, the vacant state ofthe second desk, and the occupied with human present state of the thirddesk from the sensor block; and updating a scheduler to indicate theoccupied with human absent state of the first desk, the vacant state ofthe second desk, and the occupied with human present state of the thirddesk.
 12. The method of claim 9: wherein updating the scheduler toindicate the occupied with human absent state of the first deskcomprises updating the scheduler to indicate a first location and theoccupied with human absent state of the first desk; wherein updating thescheduler to indicate the vacant state of the second desk comprisesupdating the scheduler to indicate a second location and the vacantstate of the second desk; and wherein updating the scheduler to indicatethe occupied with human present state of the third desk comprisesupdating the scheduler to indicate a third location and the occupiedwith human present state of the third desk.
 13. The method of claim 9:wherein recording the first image at the sensor block comprisesrecording a first depth image at the sensor block, the first depth imagedepicting the first desk; wherein recording the second image at thesensor block comprises recording a second depth image at the sensorblock, the second depth image depicting the second desk; and whereinrecording the third image at the sensor block comprises recording thethird depth image at the sensor block, the third depth image depictingthe third desk.
 14. The method of claim 9, wherein extracting the set offeatures associated with the first desk from the first image comprises:extracting the first set of features from the first image, the first setof features representing a first set of human effects; and associatingthe first set of features with the first desk based on proximity of thefirst set of features to the first desk in the first image.
 15. Themethod of claim 14, wherein associating the first set of features withthe first desk based on proximity of the first set of features to thefirst desk in the first image comprises associating the first set offeatures with the first desk in response to detecting the first set offeatures within a first predefined region of the first image, the firstpredefined region associated with the first desk.
 16. The method ofclaim 14, wherein associating the first set of features with the firstdesk based on proximity of the first set of features to the first deskin the first image comprises associating the first set of features withthe first desk in response to detecting the first set of features withina threshold distance of the first desk in the first image.
 17. Themethod of claim 9, wherein extracting the first set of featuresassociated with the first desk from the first image, the first set offeatures representing the first set of human effects, the first set offeatures representing the first set of human effects is selected from agroup consisting of: personal items; laptop computers; tablet computers;smartphones; keyboards; electronic mice; charging cables; data transfercables; beverage containers; food containers; utensils; tissues;napkins; pairs of headphones; articles of clothing; wearableaccessories; keys; keychains; wallets; pens; pencils; books; booklets;notebooks; and pieces of loose paper.